Telling the other what one knows? Strategic lying in a modified acquiring-a-company experiment with two-sided private information


Lying for a strategic advantage is to be expected in commercial interactions. But would this be more or less obvious when lying could come from either party and question mutually profitable exchange? To explore this, we modify the acquiring-a-company game (Samuelson and Bazerman in Res Exp Econ 3:105–138, 1985) by letting both, buyer and seller, be privately informed. Specifically, the value of the company for the buyer is known only by the seller; whereas, only the buyer is aware by which proportion the sellers evaluation is lower than that of the buyer. Before bargaining, both parties can reveal what they know via cheap-talk numerical messages. Game theoretically, the pooling equilibrium may or may not allow for trade depending on the commonly known expected evaluation discrepancy. By mutually revealing what one knows, one could boost trade and efficiency. Although strategic misreporting prevails quite generally, it is higher for sellers throughout the experiment. Regarding gender, women misreport less, especially as sellers, and offer higher prices.

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  1. 1.

    See Akerlof (1978).

  2. 2.

    This situation differs from lying to an experimenter, on which recently many researchers focussed their attention (see Fischbacher and Föllmi-Heusi 2013), since it implies lying and harming another participant.

  3. 3.

    See Samuelson and Bazerman (1985).

  4. 4.

    See as examples Fischbacher and Föllmi-Heusi (2013), using the “die throw-reporting task” and Gneezy et al. (2018) using a variation of the cheating game.

  5. 5.

    See Capraro (2018) for a review of experimental studies using the sender–receiver game.

  6. 6.

    Treatment R could appeal to global players and hedge funds whose business is to buy and sell companies and thus to trade on both sides of the market. Compared to this, Treatment C distinguishes enterprises, which mainly sell companies, and others which mainly acquire them to complete their competences. Examples are firms with focus on research and innovative output, and growing tech companies such as Amazon and Alphabet.

  7. 7.

    Specifically, our data analysis will focus only on message data \({\hat{v}}\), \({\hat{q}}\) for \(0.05<v<0.95\) and \(0.1<q<0.7\) for which both, under- as well as to over-reporting is possible, i.e., the messages for the possible values \(v=0.05; 0.95\) and the possible parameters \(q=0.1; 0.7\) are omitted as they are not fully comparable with the rest of the parameters.

  8. 8.

    We refer to strategic misreporting as \({\hat{v}}>v\), respectively, \({\hat{q}}<q\).

  9. 9.

    More specifically, gender effects in frequencies are tested via a regression where dependent variable is the frequency of truth-telling (or misreporting) of either males or females in the same matching group (periods pooled). Such aggregated frequencies are regressed on a single gender dummy to check whether they differ significantly from male to female participants. To account for dependence between the two frequencies of males and females belonging to the same group, standard errors are clustered at the matching-group level (see Moffatt 2015, pg. 84–85).

  10. 10.

    In Tables 4 and 5 the number of subjects drops when passing from the analysis of the probability of strategic misreporting to that of the extent of misreporting because in the latter we only take into account the subjects who strategically misreport (a small fraction of subjects never strategically misreport).

  11. 11.

    For the computation of loss and risk tolerance score, see Appendix. Variables easy and experienced come from the phase-3 questionnaire; they indicate, respectively, that the subject found the experiment easy and whether she participated to more than five experiments.


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Correspondence to Andrej Angelovski.

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Werner Güth: This research project was financed by the Max Planck Institute for Research on Collective Goods.



Loss and risk tolerance

Loss tolerance is elicited using the procedure proposed by Gächter et al. (2010). Figure 9 shows a screen-shot of the test.

Fig. 9

Loss tolerance test

The loss tolerance score is computed as follows:

  • for subjects who switch from participating to not participating, the score is equal to the lottery of the first switch (from 2 to 6). Therefore, the higher the lottery number, the higher the loss that the subject is willing to bear;

  • subjects who are never willing to participate to such lotteries are considered to have the lowest loss tolerance. Their loss tolerance score is set to 1;

  • subjects who are always willing to participate to such lotteries are considered to have the highest loss tolerance. Their loss tolerance score is set to 7.

Following the same rationale, the risk tolerance score, based on a Holt and Laury (2002) task, is computed as follows:

  • for subjects who switch from left (“safer”) to right (“riskier”) lottery, the score is equal to the pair of lotteries corresponding to the first switch (from 2 to 10). Therefore, the higher the lottery number, the higher the between-payoff variance that the subject is willing to bear;

  • subjects who always choose the low-variance lottery are considered to have the lowest risk tolerance. Their risk tolerance score is set to 1;

  • subjects who always choose the high-variance lottery are considered to have the highest risk tolerance. Their risk tolerance score is set to 11.

Experimental instructions

[Not part of the instructions: constant role treatment]

Welcome to our experiment! During this experiment you will be asked to make several decisions and so will the other participants.

Please read the instructions carefully. Your decisions, as well as the decisions of the other participants will determine your earnings according to some rules, which will be shortly explained below. For participating in this experiment you will receive a participation fee of 5 euros. In addition to this you can earn more or loose from this amount, based on the decisions you and others may make during the experiment. However, you will never lose all your own money, as losses cannot exceed your participation fee (5 euros). The final amount you earn during the experiment will be paid individually immediately after the experiment finishes. No other participant will learn from us how much you have earned.

All monetary amounts in the experiment will be computed in Experimental Currency Units (ECU). At the end of the experiment, all earned ECUs will be converted into euro using the following exchange rate:

$$\begin{aligned} 12\hbox { ECU}= 1\hbox { euro}. \end{aligned}$$

You will submit your decisions by clicking the appropriate buttons on the screen. All participants are reading the same instructions and taking part in this experiment for the first time.

This experiment is fully computerized. Please note that from now on any communication between participants is strictly prohibited. If you violate this rule, you will be excluded from the experiment with no payment. If you have any questions, please raise your hand. The experimenter will come to you and answer your questions privately.

After the experiment you will be asked to answer a short questionnaire; please note that the data will be treated anonymously.

Description of the experiment

Before the first round starts, each participant is randomly assigned to one of two possible roles. Half the participants will assume the role of buyer; the other half will assume the role of seller. You will remain in the same role throughout the experiment, which will last for 24 rounds. In each of several successive rounds you will be randomly matched with a different participant in the other role. For example, if you are a buyer, then you will be randomly and anonymously matched with another participant who is a seller, and vice versa.

In each round, a firm owned by the seller, may or may not be bought by the buyer. The computer will randomly select the buyer’s value of the firm, v, among the following values: 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90 and 95 (with all these values being equally likely). Although v is the buyer’s evaluation of the firm, owned by the seller, its value will be communicated only to the seller. The buyer will not learn the value of the firm which is selected randomly by the computer.

The seller’s evaluation of the firm, \(q\dot{v}\), is proportional to the buyers value of the firm, selected by the computer. The disparity coefficient, q, will be randomly selected by the computer and can only take one of the following values: 10, 20, 30, 40, 50, 60 or 70% (with all these values being equally likely). The computer randomly selects one of the 7 possible disparity coefficients q and the random result q is revealed only to the buyer. The seller will not learn which disparity coefficient is selected randomly by the computer. Thus of the seller’s evaluation of the firm, \(q\dot{v}\) of q, only the buyer knows q, whereas only the seller knows v.

As an example, suppose that the computer selects a value v of 80 and a disparity coefficient, q of 50% so that the seller’s evaluates the firm with 40, corresponding to 50% of 80 (\(0.5{\cdot }80\)). In this case, the seller will find on the screen only the value of the firm, 80, whereas the disparity coefficient of 50% is only revealed to the buyer on his screen.

Before negotiating whether to sell the firm, the seller sends a value message to the buyer about the value of the firm, which can be either true or false. Similarly, the buyer sends a disparity message to the seller which also may be true or false, i.e., the messages are not necessarily reliable. Each message is restricted to the integers which are possible for v, respectively, q, i.e., the value message can be 5, 10, 15 \(\ldots \) up to 95 and the message concerning the disparity coefficient can be 10, 20 \(\ldots \) up to 70%.

After having sent and received the respective messages, the buyer offers a price, p, to the seller which can be any integer number between 0 and 100. Having received the price proposal of the buyer, the seller decides whether to accept it or. If she accepts, the firm is sold at the proposed price, p, to the buyer. If the seller does not accept, no trade takes place.

After the seller has decided, the payoffs of buyer and of seller are calculated and individually communicated at the end of each round.

Calculation of the payoff: the payoff in each period is calculated as follows.

If the seller has accepted the offered price, the payoffs are:

  • The buyer earns the difference \(v - p\) between his value v of the firm and the accepted price p.

  • The seller earns the difference \(p - q\cdot v\) between the accepted price p and his evaluation \(q\times v\) of the firm.

If the seller rejects the offer, both the seller and the buyer earn 0 ECU.

An example: suppose the firm value (value for the buyer) is equal to 45 and that the disparity coefficient is 70%, so that the seller’s evaluates the firm 31.5 (\(0.7 \cdot 45\)). Suppose the buyer proposes a price equal to 40. If the seller accepts it, the buyer earns \(45 - 40 = 5\), and the seller earns \(40\hbox {-}31.5 = 8.5\); if the seller rejects, both earn 0.

At the end of the experiment, the computer will randomly select one round and the payoff you realized in that round will constitute your final payment for the experiment, plus a show-up fee of 8 euros.

Note that the exchange may also result in a loss for either the buyer or the seller. If you realized a loss in the round selected for payment, in any case the latter will never exceed your show-up fee.

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Angelovski, A., Di Cagno, D., Güth, W. et al. Telling the other what one knows? Strategic lying in a modified acquiring-a-company experiment with two-sided private information. Theory Decis 88, 97–119 (2020).

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  • Bargaining
  • Private information
  • Cheap talk
  • Acquiring-a-company game